Wireless communication is ubiquitous and deployments are growing rapidly. In 2008 the International Telecommunication Union estimated the number of mobile telephones at 4.1 billion with a worldwide population of approximately 6.8 billion people (ITU Corporate Annual Report, http://www.itu.int/dms_pub/itu-s/opb/conf/S-CONF-AREP-2008-E06-PDF-E.pdf). Portio Research estimates the number of mobile telephones will grow to 5.8 billion by 2013, fueled by Asia-Pacific particularly, which by 2013 will account for 43.9 percent of subscribers, followed by Europe (25.0 percent), Africa and Middle East (12.2 percent), Latin America (11.2 percent) and North America (7.6 percent) (“Mobile Factbook 2009” http://www.portiodirect.com/productDetail.aspx?pid=49$55$51$431). By 2014, global mobile Internet users expected to send and receive 1.6 Exabytes of mobile data each month, which is more than the 1.3 Exabytes transferred during the whole of 2008, according to ABI Research (http://www.abiresearch.com/press/1466-In+2014+Monthly+Mobile+Data+Traffic+Will+Exceed+2008+Total).
Cellular phones are evolving into hand-held computers with voice, data and video multimedia applications and accordingly, there is the associated increasing demand for more bandwidth. IDC estimates the annual shipment of Bluetooth-enabled devices as 1.2 billion devices and growing with 20% CAGR (http://www.idc.com/getdoc.jsp?sessionId=&containerId=219098 &sessionId=UDMGOJ2XGTN JMCQJAFICFGAKBEAUMIWD). In-Stat estimates the annual shipment of WLAN-enabled devices is 380 million and growing 24% CAGR (“Global Wi-Fi Chipset Forecast and Analysis: 2007 to 2013” http://www.instat.com/abstract.asp?id=167&SKU=IN0904005 WS). Additionally, the cost of deploying a wireless system is decreasing by half compounded every five years (The Economist, Apr. 10, 2008).
By contrast the wireless spectrum is a scarce and limited resource allocated in to many different communications and RF applications with only a few small segments for the many different communication uses associated with wireless devices by consumers and business users (see for example www.ntia.doc.gov/osmhome/allochrt.pdf). The recent auction of spectrum in the US provides a good indication of spectrum scarcity and resulting value where in 2008, the US Federal Communications Commission (FCC) auctioned a relatively tiny 62 MHz segment of spectrum across the United States for a total of US$19.6B (http://wireless.fcc.gov/auctions/default.htm?job=auction_summary&id=73) to a collection of telecommunications service providers including Verizon and AT&T. This spectrum was made available as a result of the digital television (DTV) transition away from analog TV (http://en.wikipedia.org/wiki/United_States—2008_wireless_spectrum_auction).
To satisfy the increasing demands for performance and throughput, wireless physical layer designs are becoming increasingly complex. It has been nearly thirty years since the first commercial wireless network using frequency division multiple access, so-called 1G technology was developed. Next came time division multiple access (TDMA) in 2G Global System for Mobile Communications (GSM) systems in the 1990s followed by code division multiple access (CDMA) in 3.xG systems in the early 2000s. 4G networks of Long Term Evolution (LTE) and WiMAX are currently in the planning and deployment stages and the next generation wireless local area network (LAN) 802.11n systems are pushing throughput towards 100 Mbps with Multiple-Input-Multiple-Output (MIMO) and orthogonal frequency division multiple access (OFDMA) approaches. Such modern wireless communication systems employ sophisticated RF technologies that include frequency hopping, complex modulation and packet-based transmission formats. These new data-centric wireless systems are complex to deploy, operate, maintain and monitor.
Wireless communications are increasingly subjected to radio interference. As the density of wireless devices increases so does the density of wireless base stations. To satisfy a city of millions of cellular users, each with increased cellular usage, requires a progressively denser mesh of cellular base stations, and these increasingly interfere with each other. Simultaneously corporations are increasingly deploying or expanding wireless networks. Wireless 802.11 LAN occupies the same spectrum as Bluetooth, cordless phones and microwave ovens and “must accept any interference” (en.wikipedia.org/wiki/ISM_band). In addition to these sources of unintentional interference there is the issue of RF devices transmitting with malicious intent and the requirement in some environments for real-time radio jamming of transmitter signals.
The rapid growth of deployments, scarcity of spectrum, complexity of solutions, congestion and interference are increasingly compounded problems for those deploying, managing, maintaining and monitoring wireless services. The wireless spectrum is a shared resource. Worldwide national governments not only license the use of the spectrum but must also police that spectrum. Policing ensures that those who are not authorized are not transmitting and those who have spent billions of dollars licensing portions of the spectrum have unencumbered access to those portions. Specifically, government agencies monitor the wireless spectrum within their countries to determine the occupancy within specific segments of the spectrum, to enforce allocation, to police issues pertaining to interference, and for a variety of other legal and strategic objectives.
Consequently this results in either the requirement to maintain and deploy expensive personnel and equipment to continually or periodically monitor wireless activity within a network or environment or a decision to not monitor and police the wireless spectrum. Accordingly it would be beneficial for a wide bandwidth, real-time spectrum analyzer to be provided supporting applications across geographically distributed and localized networks allowing enforcement and monitoring of regulated, sensitive, and/or problematic wireless environments
Wireless communications and networks are deployed by telecommunications service providers, governments, corporations and the home user. Service providers are challenged by the compounding problems of increased number and density of users, increased user usage, and demands for increased bandwidth. The deployment, operation and maintenance of next generation wireless services are as a result increasing the demands for test, monitoring and “visibility” of the wireless physical layer without the similar deployment issues of deploying expensive personnel and/or equipment to at best accomplish intermittent and often inadequate monitoring. Corporate and government information technology (IT) groups face similar if not worse problems in the deployment, operation and maintenance of wireless networking infrastructure where common standards, such as IEEE 802.11, result in wireless products operating in unlicensed frequency bands. Such groups therefore not only faced with issues in installing wireless local area networks (WLANs) but supporting ongoing demand for density and bandwidth whilst reducing interference from a broad range of sources which may be transitory in nature and agile in frequency.
In addition to ensuring wireless connectivity, preventing wireless connectivity has also become an issue. A growing segment of large corporate and government departments for example require the enforcement of a no-wireless policy. A no-wireless policy is intended to prevent for example the inadvertent or malicious listening of sensitive, proprietary, confidential or secret information within meeting rooms via a cell phone or an eavesdropping device. Such policy enforcement is challenged by the breadth and complexity of wireless devices, which are evolving rapidly in terms of functionality, complexity and performance.
Applications for spectrum monitoring also extend to other environments, for example the battlefield. Equipping military personnel with the means to monitor and analyze their RF environment for communication activity, signal jammers and other threats is becoming a necessity in today's world of ubiquitous wireless devices, improvised explosive devices with remote triggers, etc.
Today, these varying regulators, service provider, and groups must either deploy laboratory or hand-held spectrum analyzers that are expensive, not designed for remote interconnected deployment and centralized management, and are not designed for real-time analysis of wireless signals or exploit hand-held spectrum/signal analyzers targeted to specific narrowband environments. Neither solution addresses the requirement for a compact, low cost, wide bandwidth, real-time spectrum analyzer that may be deployed in volume across geographic regions, and provides analysis of signals that in many instances are characterized by short duration, varying frequency through frequency hopping, arbitrary frequencies, intermittent operation, and which arise in-band or out-of-band with the normal environment of other wireless signals operating according to multiple protocols, often with high density.
There is also the requirement for such real-time spectrum analysis to operate in conjunction with wireless infrastructures that ranges from macrocells characterized by large antenna tower structures spaced many kilometers apart to picocells and femtocells where network access points, base stations, are meters or tens or meters apart. The applications of such real-time distributed spectrum analysis include interference detection, no-wireless or selective-wireless policy enforcement, spectrum management, signals intelligence (SIGINT), communications intelligence (COMINT), electronic intelligence (ELINT) and signal /interference analysis.
Accordingly it would be beneficial to provide regulatory authorities, service providers as well as network operators etc. with low cost, wide bandwidth, real-time network deployable spectrum analyzers allowing geographically distributed real-time monitoring as well localized monitoring functions to be implemented. Such low cost, wide bandwidth, real-time network deployable spectrum analyzers require a high performance, wideband, fast, programmable wide frequency range RF receiver. Wireless RF communications and other microwave applications range within the United States are covered by the FCC regulations up to 300 GHz (see http://www.ntia.doc.gov/osmhome/allochrt.html for allocations) although within this document for discussion purposes and by way of illustration a frequency range from 0.10 to 8 GHz will be considered.
Considering the prior art this currently is distributed between generally large RF test equipment, from companies such as Agilent, Tektronix, Anritsu, Ando, etc., allowing measurements and analysis over a wide frequency spectrum, for example 0 MHz-6000 MHz as well as variants for hand-held use and specific test equipment addressing a particular market with limited functionality and limited frequency range as well as being pre-programmed in terms of assumptions for that market whereas RF test equipment provides increased flexibility. Considering the later then typical examples include the hand-held Agilent N9342C Handheld Spectrum Analyzer (7 GHz) with a full-band sweep of approximately 400 ms (17.5 GHz/s tuning speed) and costing approximately $13,000 and the Agilent E4404B ESA-E Spectrum Analyzer (6.7 GHz) with improved noise performance albeit at reduced sweep speed for approximately $35,000. Retail prices for other laboratory spectrum analysers may rise from approximately $10,000 to over $100,000 per instrument according to bandwidth, noise floor, etc.
Such instruments exploit scanning RF receivers based upon super-heterodyne techniques that are well known in the prior art wherein the received RF signal (RF) is mixed with a local oscillator (LO), i.e. heterodyned, converted to an intermediate frequency (IF) and processed. In a spectrum analyzer the LO is swept across the band of interest at a predetermined rate according to scanned range, resolution bandwidth, etc. Typically, such spectrum analysers in order to provide high resolution employ narrow intermediate frequencies (the output frequency from the mixer combining the LO and RF signals) that may be for example 1 kHz, 100 Hz, or 1 Hz. Such low IF being achieved through multiple heterodyne stages with multiple LO signals. A classic super-heterodyne receiver according to the prior art, see for example Agilent Technologies Application Note 150 “Spectrum Analyser Basics” (http://cp.literature.agilent.com/litweb/pdf/5952-0292.pdf) as depicted by super-heterodyne receiver 1550 in FIG. 1B.
An alternative to super-heterodyne receivers is the direct-conversion receiver (DCR) that is much simpler to implement in integrated circuit form, see for example B. Razavi in “Design Considerations for Direct-Conversion Receivers” (IEEE Trans. Circuits & Systems II—Analog and Digital Signal Processing, Vol 44(6), pp. 428-435). In a DCR the RF band of interest is translated down to the baseband in only one conversion. Other names for this receiver architecture are zero-IF or homodyne. While the shortcomings of such receivers include DC and I/Q offsets in the baseband output, the main advantages are low-cost implementation and large instantaneous bandwidth. DCRs are typically found in high volume consumer device communications chipsets for applications such as Bluetooth (IEEE 802.15) and Wi-Fi (IEEE 802.11) with a constant frequency range of operation thereby limiting the impact of these shortcomings.
Signal analysis instrumentation includes for example the N9010A EXA Signal Analyzer (7 GHz) in a laboratory instrument retailing for approximately $35,000 with ability to implement pre-determined WLAN measurement applications or operate without them for more general signal analysis. Dedicated instruments include for example Fluke AirCheck™ Wi-Fi Tester for IEEE 802.11a/b/g/n networks which provides signal monitoring across Channels 1-14 in the 2.4 GHz band (2412-2484 MHz) but only Channels 34, 36, 38, 40, 42, 44, 46, 48, 52, 56, 60, 100, 104, 108, 112, 116, 120, 124, 128, 132, 136, 140, 149, 153, 157, 161, 165 in the 5 GHz Band (5170-5320 MHz, 5500-5700 MHz, and 5745-5825 MHz) but costs $2,000.
Others include for example Berkeley Varitronics Beetle for IEEE 802.11a/b/n/g and exploit typically identical RF receiver circuits as the portable wireless devices that access the networks these devices monitor but with dedicated network analysis software controlling the receiver or discrete circuits employing elements designed for use in network infrastructure elements where cost-performance tradeoffs are different to consumer ASICs for example. Accordingly such devices employ a transceiver such as depicted in FIG. 1B by transceiver 1000.
Within the prior art spectrum analysis has been the subject of substantial research and publications leading to continuous improvements and enhancements of commercial spectrum analysers from manufacturers such as Agilent, Tektronix, Anritsu, Ando, etc. Spectrum analyzers are used in a number of different applications including signals intelligence (SIGINT), communications intelligence (COMINT) and spectrum monitoring. For such applications, the emergence of complex modulation formats, frequency hopping waveforms and packet-based, intermittent transmissions in today's communications systems has led to the requirement to monitor the spectrum over a range of frequencies in a manner that all spectral activity is captured. Conventional swept-tuned Spectrum Analyzers typically performed non-coherent signal detection over a relatively small frequency range of interest.
A Realtime Spectrum Analyzer by comparison is one that is able to sample the incoming RF signal in the time domain and convert the information to the frequency domain using a Fast-Fourier Transform (FFT) process. The range of frequencies processed in one FFT calculation is limited to the instantaneous bandwidth of the receiver. The frequency range that is processed instantaneously can be ten or more times greater than that processed by a conventional spectrum analyzer. FFTs are processed in parallel, with no gaps and overlapped so there are no gaps in the calculation. As a result all signals that appear across the instantaneous bandwidth of the analyzer are detected. When monitoring a range of spectrum that exceeds the instantaneous bandwidth of the analyzer, that real-time display is really a series of discrete time specific measurements over different frequency ranges as evident from the teaching of K. Bernard in US Patent Application 2008/0,258,706 entitled “Wide-Bandwidth Spectrum Analysis of Transient Signals using a Real-Time Spectrum Analyzer”. Bernard describes the real-time spectrum analyzer (RTSA) as operating by selection of a frequency window, the frequency window being narrower in bandwidth than the frequency spectrum of interest.
The RTSA is then successively tuned to a plurality of different frequencies within the frequency spectrum of interest, where such successive tuning is controlled based on a characteristic of the signal. The RF signal is received, and, for each of the plurality of different frequencies, power data is acquired for the signal in a band centered on the frequency and having a bandwidth equal to that of the frequency window. A representation of the frequency spectrum of interest is then constructed from the power data acquired during the successive tunings of the RTSA. Accordingly, it is necessary to know where the transient signal will appear in order for the RTSA of Bernard to capture information on the signal. It is also clear that a single transient pulse would not be captured in anything other than a measurement at the first tuned frequency of the RTSA.
Similarly, F. LaMarche et al in U.S. Pat. No. 7,957,938 entitled “Method and Apparatus for a High Bandwidth Oscilloscope utilizing Multiple Channel Digital Bandwidth Interleaving” teaches to a method of performing wide-band spectral analysis of transient signals wherein the analog signal spanning a frequency range into a plurality of frequency bands, and then translating at least one of the signals to a lower frequency band in accordance with a local oscillator and digitizing the at least one translated signal with digitizing elements having a frequency range less than the analog signal frequency range. LA Marches teaching that the sampled signal is then recirculated in a circular buffer with signals corresponding to the other of the plurality of frequency bands being similarly digitized and written to corresponding circular buffers. The digitized data from the plurality of frequency bands is then employed to re-construct the analog signal allowing for subsequent processing to generate the spectral content.
J. Earls et al in US Patent Application 2005/0,207,512 entitled “Multi-Channel Simultaneous Real-Time Spectrum Analysis with Offset Frequency Trigger” teaches a RTSA wherein a wideband IF signal derived from a wideband RF signal is provided to both a wideband IF channel and a narrowband IF channel simultaneously. The Wideband IF signal output from the Wideband IF channel is sampled at a high sample rate with relatively low resolution to produce wideband signal data. The wideband IF signal input to the narrowband IF channel is frequency offset by a variable amount according to a region in the wideband IF signal where a frequency trigger event is expected and then narrowband filtered to produce a narrowband IF signal. The narrowband IF signal is sampled at a relatively low sample rate with high resolution to produce high dynamic range signal data for input to a frequency trigger function.
Within the prior art Dong et al. in US Patent Application 2010/0,304,703 entitled “Multiple Frequency Band Hybrid Receiver” have described a receiver architecture primarily intended for communications signal processing. An example of its application is a dual-band Wi-Fi chip set operating at both 2.4 GHz and 5 GHz. In this architecture different frequency bands are input to a plurality of input terminals, in other words there is no overlap between the frequency ranges input to the different terminals. As well the lowest frequency band is associated with a direct-conversion process. All other frequency bands are down-converted to the input frequency of the mixer associated with the lowest frequency band. No pre-selector filter banks or switchable channel filters associated with the super-heterodyne stages.
Accordingly, the prior art of Bernard and Earls exploit conventional prior art super-heterodyne receivers without consideration of how that providing a true RTSA impacts the design and implementation of the RF front-end. In contrast LaMarche teaches to the use of banded super-heterodyne receivers to split a single RF input into 4 bands wherein the outputs of the multiple bands are digitized after processing to bring their RF power levels to approximately the optimum input power for the analog-to-digital convertors (ADCs). Likewise the prior art of Dong discussed above exploits prior art super-heterodyne receivers to always downconvert non-overlapping frequency bands to the lowest frequency band and accordingly frequency bands are always down-converted by a common final mixer and higher bands are down-converted multiple times to this lowest band.
In contrast, recent work by Cognio Inc., now part of Cisco Systems Inc., has considered signal analysis for determining whether to jam an unauthorized transmission occurring within a predetermined region, see for example N. R. Diener et al in U.S. Pat. No. 7,142,108 entitled “System and Method for Monitoring and Enforcing a Restricted Wireless Zone” (hereinafter referred to as Diener '108) and N. R. Diener et al in U.S. Pat. No. 7,184,777 entitled “Server and Multiple Sensor System for Monitoring Activity within a Shared Radio Frequency Band” (hereinafter referred to as Diener '777). Diener '108 teaches that at each location within the predetermined region a spectrum monitoring section analyses all activity within a narrow predetermined band, e.g. 2.400-2.483 GHz ISM, 5.725-5.825 GHz Upper U-NII (U-NII-3) band for example, based upon applying a Fast-Fourier Transform (FFT) to received pulsed signals with multiple FFT intervals to determine a power versus frequency plot. This data is then sent, using a different frequency range and transmission standard, to a central server for every cycle of the FFT process along with additional information derived from a co-hosted traffic monitoring station that operates using International standard protocols, such as IEEE 802.11, to generate probe requests and receive responses allowing legitimate traffic to be identified or transmitting nodes operating according to the International standard to be located.
Each of Diener '108 and Diener '777 utilize a spectrum analysis engine (SAGE) as described by G. L. Sugar et al in U.S. Pat. Nos. 6,714,605 and 7,224,752 entitled “System and Method for Real-Time Spectrum Analysis in a Communication Device”; Sugar et al in U.S. Pat. No. 7,254,191 entitled “System and Method for Real-Time Spectrum Analysis in a Radio Device”; and D. Kloper et al in U.S. Pat. No. 7,606,335 entitled “Signal Pulse Detection Scheme for Use in Real-Time Spectrum Analysis.” The SAGE also providing spectral analysis for other aspects of management of wireless infrastructure taught by Cognio including U.S. Pat. Nos. 6,850,735; 7,269,151; 7,079,812; 7,116,943; 7,171,161; 6,941,110; 7,035,593; U.S. Pat. Nos. 7,110,756; and 7,292,656 as well as US Patent Application 2003/0,198,200; 2007/0,264,939; and 2008/0,019.464.
As presented by Sugar and Kloper the SAGE is presented as a hardware accelerator to determine information about pulses occurring within a predetermined frequency range, determined in dependence upon the wireless network that the SAGE is monitoring, and provides information to network infrastructure elements allowing network management activities to be performed, these being the subject of the other patents identified above in respect of Cognio although it would be noted that other prior exists in respect of managing networks based upon determined characteristics of activity within the network. The SAGE, as described in respect of FIG. 2 below, does not consider any aspect of the design of the RF front-end apart from an RF interface which adjusts the gain provided to the received RF signal such that the maximum signal received in the last T seconds (for example 1 second) is 6 dB below the full-scale of the analog-to-digital converter (ADC) within the RF interface.
The digitized RF signal from the RF interface, actually the digitized IF signal received, is windowed and processed with a Fast-Fourier Transform (FFT) to convert the digitized signal to the frequency domain. The FFT processed IF signal is then coupled to a plurality of peak detectors and pulse detectors which make decisions based upon predetermined characteristics of signals anticipated as present within the network, i.e. the pulse has a predetermined width. The decisions from the pulse detectors and peak detectors are then used through a series of rules to determine whether the SAGE will capture a portion of the received RF signal and/or forward the power measurements to memory. The SAGE only captures on a consistent basis statistical data from the FFT. Accordingly, signals outside the pulse detector configurations, which are for predetermined signal types, are not captured or analysed except to increment counters within the frequency bins associated with the FFT results.
Further, the SAGE via a Universal Signal Synchronizer establishes timing synchronization of the pulse detectors etc. to the network being monitored. Accordingly, signals occurring out of synchronization are not analysed correctly such as those for example arising from another transmitter operating according to the same standard but on different time base and a transmitter on a different timing for transmissions Likewise aperiodic frequency hopping signals would not be captured. This inherent timing and synchronization reflects the focus of the work of Cognio to narrowband (100 MHz) standard communications bands, such as those relating for example to IEEE 802.11b, IEEE 802.11g and IEEE 802.16e. As a result the SAGE does not actually perform real-time analysis of the RF spectrum in the wireless environment being monitored as decisions are based upon the determination that events conforming to predetermined criteria have occurred which are based upon determining pulse characteristics that may be for example 4.6 ms in GSM, 5 ms in WiMAX (IEEE 802.16) or variable in Wi-Fi (IEEE 802.11).
Today multiple networks are operating simultaneously within the environment of a user who may for example be working at their laptop with a Wi-Fi wireless router (e.g. 5.775 GHz U-NII-3 based IEEE 802.11) interfaced to the Internet whilst talking using a Bluetooth (unlicensed 2.4 GHz) headset to a Voice-over-IP (VOIP) with their Research in Motion™ Blackberry operating at 1.9 GHz on GSM. Accordingly, interference on one device may arise from sidelobes of signals transmitted in other bands from other devices. Accordingly, to determine such effects, monitor legitimate activity, identify rogue transmitters, networks etc. as discussed supra along with other enforcement/monitoring/proactive applications it would be beneficial to cost-effectively monitor geographical areas for signal activity within multiple frequency bands over a wide frequency range whilst providing the ability to do so truly in real-time such that even very short intermittent transmitters are identified in applications that are sensitive to such signals from security, control, or prevention issues for example.
However, as with most RF and high speed electronics this desired increase in instantaneous bandwidth (IBW), real-time processing and operating frequency range (for example 0-8 GHz) produces a dilemma because the operating frequency range of the RTSA is primarily related to RF amplifier design, filter design and semiconductor technologies whilst the processing speed and IBW are determined through a combination of the RF front-end, ADCs, FFT processing, etc. and hence are impacted by both analog and digital portions of the RTSA. The RTSA-like laboratory and held-held spectrum analysers would traditionally be designed using custom application specific integrated circuits (ASICs) for the analog portions and high speed field programmable gate arrays (FPGAs) for the digital portion. These ASICs and FPGAs typically being built utilizing the higher performance integrated circuit (IC) design processes and manufacturing available. In other words, the RTSA is essentially built in and uses different processes and designs to the transceiver circuits that broadcast the RF signals that the RTSA is designed to monitor. This is very different from spectrum and protocol analysers addressing specific telecommunications standards that can typically leverage the same ASICs and other circuit elements of devices operating according to those standards, such as cellphones, smartphones, PDAs, etc.
High speed FPGAs and custom ASICs are expensive and in some instances difficult to utilize. In high volume consumer applications such as Wi-Fi (IEEE 802.11), WiMAX (IEEE 802.16) and Bluetooth the transmitter circuits and receiver circuits are typically implemented with silicon based digital IC designs and processes whereas the RTSA is optimized towards to both digital and analog aspects for high performance measurement applications wherein it is beneficial to leverage new IC design processes optimized to aspects such as faster computational processing, improved serial data links, etc. as well as RF circuit integration rather than accepting performance tradeoffs, whilst meeting a wireless specification, in order to provide monolithic integration and exploit lower cost IC processes.
It has been determined by the inventors of the present invention that a hybrid receiver architecture can be combined with digital based back end processing to satisfy the conflicting requirements of low-cost, high speed, wide IBW, large operating frequency range, and high sensitivity so that they can be balanced within a field-deployable network interfaced module wherein deployed volumes whilst significantly larger than laboratory based test equipment will not reach by orders of magnitude the volumes of the RF transmitters they are monitoring. This is not to say that such receivers won't find utility in other signal analyzer applications.
Accordingly, based upon embodiments of the invention, the inventors have established a low cost, broadband, real-time signal analyzer circuit that allows for the deployment of such RTSA devices in a distributed environment wherein determination of policy breaches, network performance, regulatory compliance, etc. are locally determined and exploited directly in network management or communicated to the central server and network administrators for subsequent action. Beneficially the RTSA according to embodiments of the invention provides for a scalable architecture wherein multiple RTSA modules may be synchronized providing enhanced spectral bandwidth, processing speed, and monitoring.
However, it would be apparent that such a hybrid receiver providing low-cost, high speed, wide IBW, large operating frequency range, and high sensitivity would have a wide range of applications including, but not limited to, spectrum analysers, protocol receivers, frequency agile receivers and transponders, network management, and EMC testing. It would further be evident that the deployment context of devices employing such hybrid receivers may include, but not be limited to, laboratory environments, remote stand-alone deployments, integration or deployment with other network infrastructure, hand-held or field-test deployments, as well as part of other civilian, Governmental and military systems and platforms.